replikativ/datahike
Versioned, fast, distributed Datalog engine for everyone. observed · 2026-08-28
Health v2 · maintenance only
95/100
- Activity 99
- Release rhythm 87
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 0.0
- age_days: 3162
- days_rel: 7
- days_push: 7
- n_releases_24m: 221
Adoption not part of the score
1864 stars · 118 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Datahike is a durable, versioned Datalog database with Datomic-compatible APIs and git-like semantics, built on persistent data structures so every transaction yields an immutable, shareable snapshot. It supports time-travel queries, GDPR-compliant data excision, pluggable storage backends (file, LMDB, S3, JDBC, Redis, IndexedDB), and direct reader access to storage without a server.
Use cases
- embed a Datomic-compatible Datalog database in a Clojure application
- query historical states of a database with time travel
- store application data directly in S3 without running a database server
- build auditable data pipelines with a full transaction history
- implement GDPR-compliant data purging with a verifiable audit trail
- share immutable database snapshots between teams via a common S3 bucket
- give long-running AI agents a versioned memory substrate
- query graph-like relationships with recursive Datalog rules instead of SQL joins
When to choose
- you want Datomic-style Datalog semantics without Datomic's licensing or server requirements
- you need immutable snapshots, branching, and time-travel queries as first-class features
- you want readers to query storage (S3, filesystem) directly without a database server
- you need GDPR-compliant data excision with an audit trail
- you're building Clojure/ClojureScript apps that share one data model across JVM, Node, and browser
When to avoid
- you need heavy concurrent write throughput with centralized transaction coordination
- your team is SQL-first and Datalog's rule-based querying would be a hurdle
- you require a mature ecosystem of ORMs, admin tools, and managed hosting
- you need strict ACID guarantees across a distributed cluster with multi-master writes
Facets
library · maturity active
database search-engine vector-database serialization databases developer-tools large-language-models microservices jvm jvm-scripting browser cross-platform self-hosted datalog datomic-compatible immutable-database time-travel git-like-branching embedded-database konserve gdpr merkle-verified clojure clojurescript persistent-data-structures nodejs
4 sources
- readme: https://github.com/replikativ/datahike · fetched 2026-08-28 · 395c9203d61a
- homepage: https://datahike.io · fetched 2026-08-29 · cd7df0405480
- site_page: https://datahike.io/about · fetched 2026-08-29 · 9e6e129de0bf
- site_page: https://datahike.io/proximum · fetched 2026-08-29 · 6768c40739da
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| replikativ/datahike | main | 95 |
For agents
markdown · JSON · MCP: product_card(name="replikativ/datahike")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem